A Comprehensive Dynamic Life Cycle Assessment Model: Considering Temporally and Spatially Dependent Variations

Int J Environ Res Public Health. 2022 Oct 27;19(21):14000. doi: 10.3390/ijerph192114000.

Abstract

Life cycle assessment (LCA) is a widely-used international environmental evaluation and management method. However, the conventional LCA is in a static context without temporal and spatial variations considered, which fails to bring accurate evaluation values and hinders practical applications. Dynamic LCA research has developed vigorously in the past decade and become a hot topic. However, systematical analysis of spatiotemporal dynamic variations and comprehensive operable dynamic models are still lacking. This study follows LCA paradigm and incorporates time- and space-dependent variations to establish a spatiotemporal dynamic LCA model. The dynamic changes are classified into four types: dynamic foreground elementary flows, dynamic background system, dynamic characterization factors, and dynamic weighting factors. Their potential dynamics and possible quantification methods are analyzed. The dynamic LCA model is applied to a residential building, and significant differences can be observed between dynamic and static assessment results from both temporal and spatial perspectives. This study makes a theoretical contribution by establishing a comprehensive dynamic model with both temporal and spatial variations involved. It is expected to provide practical values for LCA practitioners and help with decision-making and environmental management.

Keywords: buildings; dynamic life cycle assessment (DLCA); environmental impact assessment; space-dependent; spatiotemporal variations; time-dependent.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Life Cycle Stages*
  • Models, Biological*

Grants and funding

This study is financially supported by the National Natural Science Foundation of China (Grant No. 71901062) and the Natural Science Foundation of Jiangsu Province, China (Grant No. BK20190377 and BK20200782).